Survey on Different Methods on Mammogram Image Classification

The image processing is utilized to convert the image nature to improve and enhance the image for human interpretation. Image processing also used to render images for machine perception. Image segmentation is a technique which has opened a wide field of methods to analyze data, which could be in the form of images, videos. This becomes useful in breast cancer detections as images are used to extract features from the region of interest in the provided mammogram. Mammography tests have been identified as a potential source for pre-detection of a cancerous cell and thus, detection done with the technique of image segmentation has been proven effective in early diagnosis of breast cancer. This paper describes the different types of image preprocessing on mammogram images, followed by image classification using different pattern classifiers can be utilized to achieve an efficient diagnosis of breast cancer. The analysis shows that there is still sufficient scope of improving efficiency and accuracy of the classification techniques available.